Multiphase Simulation Research Articles

The role of viscoplastic drop shape in impact

The impact of fluid drops on solid substrates is a cardinal fluid dynamics phenomenon intrinsically related to many fields. Although these impacting objects are very often non-spherical and non-Newtonian, previous studies have mainly focused on spherical Newtonian drops. As a result, both shape and rheological effects on the drop-spreading dynamics remain largely unexplored. In the present work we use a mixed approach combining experiments with multiphase three-dimensional numerical simulations to extend the work reported by Luu & Forterre (J. Fluid Mech., vol. 632, 2009, pp. 301–327) by highlighting the fundamental role of shape in the normal impact of viscoplastic drops. Such complex fluids are highly common in various industrial domains and ideally behave either like a rigid body or a shear-rate-dependent liquid, according to the stress solicitation. Spherical, prolate, cylindrical and prismatic drops are considered. The results show that, under negligible capillary effects, the impacting kinetic energy of the drop is dissipated through viscoplastic effects during the spreading process, giving rise to three flow regimes: (i) inertio-viscous, (ii) inertio-plastic, and (iii) mixed inertio-visco-plastic. These regimes are deeply affected by the drop initial aspect ratio, which in turn reveals the possibility of using drop shape to control spreading. The physical mechanisms driving the considered phenomenon are underlined by energy budget analyses and scaling laws. The results are summarised in a two-dimensional diagram linking the drop maximum spreading, minimum height and final shape with different spreading regimes through a single dimensionless parameter, here called the impact number.

Realistic fuel spray modeling for gasoline direct injection engine applications

Fuel spray modeling plays a critical role during modern gasoline direct injection (GDI) engine development due to fuel injection’s dominant impact on engine performance and emissions as well as the complex physical processes involved. In engineering three-dimensional (3D) computational fluid dynamics (CFD) simulations, the liquid-phase fuel atomization, evaporation, and mixing are usually modeled with the discrete droplet model (DDM) adopting a Lagrangian approach for multiphase CFD simulations. To this end, general practices heavily depend on the reduced order characterization of the injector nozzle flow. However, such simplified injector modeling may lead to insufficient representations of the complex spray dynamics. To tackle this problem, this study proposes a novel workflow to numerically evaluate GDI sub-cooled and flash-boiling sprays under engine-relevant conditions using a side-mounted GDI injector together with real gasoline fuel properties. The workflow introduces a one-way coupling (OWC) method leveraging high-fidelity nozzle flow simulations to provide realistic boundary conditions to the Lagrangian injector model. The proposed workflow was first verified in a constant volume chamber (CVC) environment and then implemented in a practical GDI engine setup to study spray morphology, fuel-air mixing, and wall-wetting propensity. In addition, detailed comparison was performed between the OWC method and the conventional rate of injection (ROI) routine. Quantitative analysis of spray characteristics was conducted to highlight possible source of discrepancies of the conventional ROI method.

Droplet-gas interactions in nanoelectrospray multiphase flow

Electrospray (ES) is production of a charged droplet plume that transits from an electrically biased supply capillary to a counter electrode under the influence of an electric field. Drag interactions with the surrounding gas decelerate the droplets while transferring the momentum from droplets to accelerate the surrounding gas, resulting in an induced gas flow. This work seeks to characterize the structure of the resulting gas jet and identify the key mechanisms defining the flow structure. The phenomenon of gas jets produced by momentum transfer from nano-electrospray (nES) plumes is explored with schlieren visualization, thermal anemometry, and numerical simulations. Schlieren visualization experiments provide information on the flow structure in support of simulation predictions, and the hot thermistor anemometry measurements of gas velocities outside the spray demonstrate quantitatively validated simulation results. The study reveals the formation of a moderately high velocity coaxial gas jet within the nES plume and provides insight into the overall flow structure of the induced flow. The multiphase electrohydrodynamic simulations enable numerical experimentation to explore the fundamental physics of coupled droplet-gas transport and the resulting flow structure. The simulations, confirmed by the experiments, reveal gas jetting induced by nES with a narrow (sub hundred micrometers in diameter) core originating from the nES liquid-jet breakup region and a surrounding larger-in-extent zone (several hundred micrometers in diameter) of lower velocity gas flow within the electrospray plume. This behavior is due to nES ejecting a stream of droplets from the tip of a narrow liquid cone-jet, where the combined effect of many small droplets transferring momentum to a confined region of gas yields a narrow but high-velocity gas stream. The micro-jets produced by nES have practical utility for mass spectrometry, 3D printing and fabrication, and thermal management.

Optimization-based level-set re-initialization: A robust interface preserving approach in multiphase problems

In spite of its overall efficiency and robustness for capturing the interface in multiphase fluid dynamics simulations, the well-known shortcoming of the level-set method is associated with the lack of a systematic approach for preserving the regularity of the distance function. This is mainly due to the stretching (or compressing) effect of the strain rate especially in the vicinity of the liquid-gas interface. Level-set re-initialization is an effective treatment for this issue. However, the traditional approach based on the hyperbolic Hamilton–Jacobi equation is a computationally expensive procedure. Crucially, due to the hyperbolic nature of the formulation, the accuracy of the results hinges significantly on the specialized handling of blind spots near the liquid-gas interface intersecting the substrate. The present work proposes a two-step elliptic level-set re-initialization approach that strictly preserves the location of zero level-set via incorporation of an element splitting process. The primary initialization step helps remove any non-smoothness in the to-be regularized level-set function dramatically improving the efficiency of the secondary optimization step. Geometric representation of the boundary conditions is utilized in the initialization step, while the optimization step minimizes the reliance of the results on the treatment of the blind spots. The performance of the proposed method is examined for free and sessile three-dimensional droplets.

Batch process monitoring based on sequential phase division multiway sparse weighted neighborhood preserving embedding

Batch processes are often characterized by multiphase and different batch durations, which vary from phase to phase presenting multiple local neighborhood features. In this paper, a sequential phase division-multiway sparse weighted neighborhood preserving embedding method is proposed for monitoring batch processes more sensitively. First, batches with uneven durations are synchronized, and the phases are automatically determined in chronological order. Secondly, the nearest neighbors are computed at each phase and the optimal sparse representation (SR) is obtained based on the nearest neighbors. This improves the robustness of the algorithm to noise and outliers, and solves the problem of computational difficulties associated with global SR based. Thirdly, the distance values of the neighbor elements are considered to fully extract the neighbor structure when the optimal SR is calculated. Finally, after dimension reduction, T 2 and squared prediction error statistics are established in feature space and residual space respectively for fault detection. The effectiveness of the method is verified by a multiphase numerical simulation example and the penicillin fermentation process.

An investigation of the cavitation and vibration phenomena in a cylindrical cyclone

Cylindrical cyclones are a popular choice for oil-water separation and sewage treatment in the petroleum industry. Here, we investigate the cavitation and vibration phenomena in a cylindrical cyclone with a vortex finder by using various cyclone operating parameters and conducting multiphase flow numerical simulations. The lowest point of pressure on the cross section of the main cylinder is defined as the pressure center point and is used to understand the generation of the flow field oscillation, which is shown to exhibit an approximately circular motion. This circular oscillation of the flow field is an important characteristic that influences the overall performance and behavior of the cyclone system. Cavitation analysis results show that an increase in the inlet velocity leads to more intense cavitation and an expansion of the cavitation area. At lower split ratios, cavitation primarily occurs at the junction of the inlet pipe and the main cylinder, while at higher split ratios, the cavitation area gradually extends into the overflow pipe. Additionally, structural response analysis demonstrates that increasing the inlet velocity and overflow split ratio significantly enhances the vibrational degree of the structure, leading to greater stress levels. Adjusting the oil content at the inlet has a relatively minimal impact on the structural response compared with the influence of the inlet velocity and split ratio. Furthermore, dimensional analysis is used to analyze the change of wall pressure, and the wall pressure that induces structural vibration can be calculated using the inlet velocity and the split ratio.

Multiphase simulation of sustainable nanoenhanced ionic liquid coolants for improved thermal performance in Ti–6Al–4V alloy drilling

Extensive research has been conducted by the manufacturing industry to enhance the efficiency of drilling processes by focusing on the utilization of nanoenhanced cutting fluids that possess excellent heat conductivity. Due to their eco-friendliness and adaptability of physical and chemical properties, ionic fluids offer enormous potential for application as cutting fluids. This study investigates the computational fluid dynamics analysis of the heat transfer performance of various ionanofluid pairs dispersed with nanoparticles as cutting fluids in the drilling process using Ansys Fluent software. For this purpose, 1-Hexyl-3-methyl-imidazolium-tetrafluoroborate is considered the ionic fluid, and its thermal behavior is examined by dispersing it with nanoparticles of copper, silver, and multiwalled carbon nanotubes (MWCNT) at different particle volume fractions and Reynolds numbers. The workpiece is composed of an alloy of titanium Ti–6Al–4V, while the drill bit is made of tungsten carbide-cobalt. It is observed that the ionic nanocoolant mist emanates from the spray tip and moves towards the drill bit-workpiece interface. Initially, the coolant's velocity is greatest close to the orifice, and as time passes, it approaches the drilling space. The data indicates that the spraying velocity of the coolant augments over time and that it disperses heat at the tool-chip interface. The results help us validate the flow and interaction of ionanocoolant with the drilling zone. With a rise in the volume fraction of added nanoparticles and Reynolds number, the results indicated a significant decrease in the drilling temperature. With a higher particle volume fraction, the MWCNT-ionic coolant combination decreases the drilling temperature of pure ionic liquid by 25.64 %. The copper, silver, and MWCNT ionanofluids enhance the average heat transfer coefficient of pure ionic coolant by 35.14 %, 47.42 %, and 62.75 %, respectively. In addition, MWCNT nanocoolants demonstrated improved thermal performance and heat removal rate in comparison to copper and silver ionanocoolants.

Sessile super-droplets as quasi-static wall deformations in direct numerical simulation of turbulent channel flow

Condensation is an important aspect of many flow applications due to the ubiquitous presence of humidity in the air at ambient conditions. For direct numerical simulations of such flows, simulating the gas phase as a mixture characterized by temperature and humidity coupled by the latent heat release and absorption has been shown to yield results consistent with multiphase direct numerical simulations at reduced cost. In the case of surface condensation, the deposition of condensate droplets represents an additional mechanism for flow modification. Extending the single-phase approach by tracking the mean deposition rates and consolidating the condensate mass into static super-droplets reintroduces the effects of surface droplets on the flow while retaining the computational advantages of simulating only the gas phase. Results of simulations of turbulent flow through a cooled, vertical channel with and without such droplets illustrate the additional effects captured compared to the original approach. In the immediate vicinity of a super-droplet, turbulent heat and vapor transport towards the cooled wall is enhanced. Direct impingement and deflection of the flow on the super-droplet cause a qualitative change in the distribution of the condensation rates, increasing on the surface of the super-droplets and decreasing in the surrounding regions. This modification of the near-wall transport leads to increased global cooling and drying efficiency compared to a smooth channel.

Multi-phase simulation for understanding morphodynamics of gravel beaches

This paper presents the use of an Eulerian–Eulerian multi-phase model to examine sediment transport over a gravel beach under regular waves. A previously published full-scale experiment is reproduced numerically; the simulated wave deformation, flow velocity, pore pressure, and morphological evolution are consistent with measurements. The multi-phase model can produce berm formation for smaller waves and beach erosion for larger waves as observation in previous field studies. The sensitivity analysis suggests that the nonlinear component of drag has significant effect on the berm formation through infiltration and exfiltration. The two simulated forces applied on the sediment (drag and buoyancy) are examined. The drag is the main force directly for sediment transport; therefore the sediment transport rate has high correlation with depth-averaged flow velocity. The buoyancy that is caused by plunging flow impacting beach face can push the sediment landward in the bore front, where the flow acceleration has its peak. The flow acceleration is considered in some previous sediment transport models empirically for simulating morphological evolution of gravel beach under waves. The buoyancy links the flow acceleration and sediment transport rate in the bore front.

On understanding the cutting mechanism of SiCp/Al composites during ultrasonic elliptical vibration-assisted machining

SiCp/Al composites play a significant role in achieving equipment lightweight, but its mechanical properties weaken the machinability. Ultrasonic elliptical vibration-assisted machining (UEVM) is a potential way to improve the machinability of difficult-to-cut materials, provides an efficient and precise solution for SiCp/Al composites in industrial manufacturing. However, the removal mechanism of SiCp/Al composites during UEVM and the effective guidance for practical machining are rarely investigated. In this paper, the cutting mechanism of SiCp/Al during UEVM is analyzed through theoretical analysis, finite element (FE) simulation and systematic experiments. Specifically, a multi-phase 2D microscopic FE simulation model is implemented and verified through systematically scratching tests. The research results indicate that particle stress distribution is influenced by variable tool-particle relative position during UEVM, promoting particle fracture and forming high-density zone of broken particles. Segmented chips with shorter length and greater curvature are the main form during UEVM, and dense layered structure appears on free surface of chips. Surface defects include cavities, crushing particles and scratches, while subsurface damage is dominated by pits and crack invasion. In addition, removal rate affects the surface formation, especially under very low scratching speed. Higher scratching speed weakens the ability of particle crushing under vibration effect, which is not helpful for improving surface integrity. Therefore, a reasonable cutting speed of 200 mm/min should be set during UEVM. This paper brings in a deeply understanding on cutting mechanisms of SiCp/Al composites, provides a theoretical guidance for the design and optimization of the vibration assisted processing of metal matrix composite.

High-energy continuous wave laser ablation of alumina ceramic

The development of high-energy continuous wave (CW) laser has enabled the generation of output powers ranging from 300 to 500 kW. Understanding the ablation mechanism of CW lasers at high laser fluence is crucial for the design of effective high-energy laser protection materials. We note that the particle-like impurities present in the protective coating material can induce defects on the ceramic-like target surface during high-energy CW laser ablation, which can alter the laser absorptivity and manifest a completely different ablation mechanism. Here, we systematically investigate the mechanism of high-energy CW laser ablation of alumina ceramic, with a specific focus on the roles of defect induction, energy transfer, and impact sputtering in the dynamic ablation of target. Specifically, the transient processes between high-energy CW laser and ceramic target will be investigated in terms of the evolution results of the ablation region, the microscopic characteristics of the ablated material, the high time-resolved on-line monitoring, and the multiphase hydrodynamics simulation. Finally, the transparent property of molten alumina ceramic to laser is proved to allow for penetrating damage to ceramic-metal composites.

Predictive Model for Relative Permeability Using Physically-Constrained Artificial Neural Networks

Summary Hysteresis of transport properties like relative permeability (kr) can lead to computational problems and inaccuracies for various applications including CO2 sequestration and chemical enhanced oil recovery (EOR). Computational problems in multiphase numerical simulation include phase labeling issues and path dependencies that can create discontinuities. To mitigate hysteresis, modeling kr as a state function that honors changes in physical parameters like wettability is a promising solution. In this research, we apply the state function concept to develop a physics-informed data-driven approach for predicting kr in the space of its state parameters. We extend the development of the relative permeability equation-of-state (kr-EoS) to create a predictive physically-constrained model using artificial neural networks (ANNs). We predict kr as a function of phase saturation (S) and phase connectivity (χ^), as well as the specific S-χ^ path taken during the displacement while maintaining other state parameters constant such as wettability, pore structure, and capillary number. We use numerical data generated from pore-network modeling (PNM) simulations to test the predictive capability of the EoS. Physical limits within S-χ^ space are used to constrain the model and improve its predictability outside of the region of measured data. We find that the predicted relative permeabilities result in a smooth and physically consistent estimate. Our results show that ANN can more accurately estimate kr surface compared to using a high-order polynomial response surface. With only a limited amount of drainage and imbibition data with an initial phase saturation greater than 0.7, we provide a good prediction of kr from ANN for all other initial conditions, over the entire S-χ^ space. Finally, we show that we can predict the specific path taken in the S-χ^ space along with the corresponding kr for any initial condition and flow direction, making the approach practical when phase connectivity information is unavailable. This research demonstrates the first application of a physics-informed data-driven approach for the prediction of relative permeability using ANN.

Analysis and optimisation of mixing in binary droplet collisions

The collision of binary droplets plays a key role in several industrial, chemical and biological processes. In these processes, the quality of the desired outcome is strongly dependent on the mixing of the liquid droplets as they collide in mid-air. In this work, multiphase direct numerical simulations based on the volume-of-fluid method have been used to investigate the process of mixing and analyse the effects of parameters such as injection velocity, timing and collision angles. The evolution of mixing due to convection and irreversible diffusive processes has been quantified by means of the segregation parameter. To synthesise the outcome of a collision, the impact parameter has been redefined to account for the collision of non-spherical droplets. It has been found that the optimal mixing does not occur for symmetric head-on collisions, but rather at moderately asymmetrical configurations. This behaviour has been explained by analysing the velocity gradient tensor. It has been demonstrated that by breaking the symmetry, the local topology of the flow is altered and the resulting convective flows increase the contact area between the liquids, thereby augmenting the mixing process. However, it was also observed that lateral misalignment transforms the initial kinetic energy into the spinning of the merged droplets, thus preventing an enhanced mixing.

Multi-Phase Equilibrium Model of Oxygen-Enriched Lead Oxidation Smelting Process Based on Chemical Equilibrium Constant Method

With the increasingly complicated sources of lead smelting materials, it is becoming more difficult to optimize process parameters during the bottom-blowing lead oxidation smelting process. Building a bottom-blowing lead smelting thermodynamic model has significant importance for the green production of the lead smelting process. In this study, we built a multi-phase equilibrium thermodynamic model and simulation system for the oxygen-enriched bottom-blowing lead oxidation smelting process using the MetCal software platform (MetCal v7.81) according to the chemical equilibrium constant method. The equilibrium products composition and important technical indicators were calculated under factory operating conditions. Compared with the industrial data, the calculation results demonstrated that the average relative error of the calculation value of the mass fraction in the crude lead, lead-rich slag, and dust was 3.76%. The average relative error of important technical indicators, including dust rate, crude lead yield, lead-rich slag temperature, slag iron–silica ratio (RFe/SiO2), and slag calcium–silica ratio (RCaO/SiO2), was 6.39%. As a result, the developed modeling and simulation system was able to reflect the current state of the oxygen-enriched bottom-blowing lead smelting. It also demonstrated the potential to enhance the smelting process and optimize the process parameters. Therefore, it is expected to provide a useful tool for thermodynamic analysis.

Minerals Dissolution Effect on the Mechanical Properties of Synthetic Carbonate Rocks

Injection of CO2 and water in saline aquifers or oil reservoirs causes changes of pressure, saturation and concentrations that affect the state of stress and promote chemical reactions in the host rock, resulting in porosity and permeability variations. It is therefore a coupled hydro-mechanical and chemical (HMC) problem. Numerical simulation of multiphase and multicomponent flow of CO2, oil and water with mechanical coupling allows realistic modeling of the reservoir and cap rocks. Carbonate reservoirs are geological formations composed mainly of minerals such as calcite and dolomite which can dissolve or precipitate in the medium when injecting a fluid of chemical composition and temperature different from those of the fluids initially contained in the rock. Water-weakening due to matrix acidification of carbonates is a well-known phenomenon that can be modeled by including mineral concentrations as state variables in the stress-strain behavior of the material.
 The objective of this work is to characterize synthetic carbonate rocks through microtomography and petrography techniques, focusing on a comparative analysis before and after load application and degradation with a reactive fluid [1]. The synthetic rocks were subjected to physical characterization (mineralogy, computed tomography and porosity) and mechanical characterization (uniaxial compressive strength and Brazilian tests) before and after the dissolution process. The petrographic analysis verified an increase in both intergranular and intragranular porosities after dissolution. The microtomography analysis quantified the maximum increase in porosity, from 11.8% to 41.3% in the two-dimensional analysis and 31.6% to 52% in the three-dimensional analysis of the porous structures. Furthermore, the pores were quantified according to their area, and data was obtained on the orientation of the pores, providing insight into the preferred paths of fluid flow. It was also observed that the microtomography technique was an effective tool for characterizing fractures in the samples before and after dissolution [1].
 Dissolution tests were also performed in a modified oedometer cell adapted to measure horizontal stress. The dissolution phase was conducted using water and an acid solution to evaluate the influence of the pH on the mechanical behaviour of the samples. When the sample in the oedometric cell is exposed to an acid solution under constant vertical load of 400kPa, vertical displacement takes place (volume decrease of the sample) and horizontal stress increases (Figure 1). The synthetic rock used in this experiment is mainly composed by calcite, with small additions of calcium hydroxide, and the reactive fluid is water acidified with acetic acid (with 10% concentration). This material is manufactured in laboratory in order to have greater control of its constituents and reproducibility of experimental results. During the acidification phase of the experiment, the sample was subjected to an acid flow with a pressure differential of 12kPa for 7h. The behavior in Figure 1 was also observed by [2] and [3]. The model for degradation of carbonatic soft rocks proposed by [2] was implemented in a finite element code capable of performing coupled THMC analyzes in porous media [4]. This model is based on the Critical State Theory with the introduction of a bonding variable that controls the size of the yield surface by modifying the tensile strength and the pre-consolidation stress of the material. In Figure 1 it is also possible to see that the HMC coupled simulation of the oedometric test was able to reproduce the experimental results in terms of volumetric strain and horizontal stress. In Figure 2 tomographic images of the synthetic carbonate rock before and after exposure to the acid solution in an oedometric cell under constant vertical load are presented. Such analyses are crucial for the injection of reactive fluids, such as CO2, at high depths. Dissolution of minerals will affect not only the porosity and permeability of the reservoir rock but also, possibly, the stress state in the vicinity of the injection well.

Modeling of electromagnetic influences of multi-wire traction networks for pipelines

In this work, digital models for determining the electromagnetic influences of multi-wire traction networks on pipelines are developed. When developing models, an approach based on multiphase behaviour simulation of electric power systems was used. This approach adequately addresses all the influencing factors, which include modules and phases of currents flowing through the overhead contact wire suspension, 6–10–25 kV power transmission lines laid on the supports of the overhead line, and lines of rails. In addition, it is possible to take into account similar parameters for stresses at the nodal points of a multi-wire system. Among the key factors are the railway clearance when laying pipes parallel to the railway track, railway clearance trajectory in the presence of non-parallel sections, and the electrical characteristics of the soil along the clearance route. The research results demonstrated that a 25 kV electromagnetically unbalanced traction network exerts significant influence on a pipeline running in parallel. It was shown that the maximum induced voltages at specific points along the pipe fall within the range of 300–700 V, which significantly exceeds the permissible level of 60 V. It was revealed that currents exceeding 20 A flowing through the pipe can have an adverse effect on anticorrosive protection devices. To mitigate electromagnetic impacts on the pipeline, the following measures are recommended: reducing the length of pipeline and railway clearance sections, increasing the gap between the traction network and the pipe, and installing an additional grounding source. The pipe can be connected to the supplementary grounding source through filters tuned to a frequency of 50 Hz, which involve capacitor units to prevent malfunctions during the operation of pipeline protection devices. Thus, the developed digital models allow the induced voltages generated by multi-wire traction networks and the currents flowing through the pipes to be adequately determined. These models offer an informed choice of measures that ensure the safety of pipeline maintenance.

Large eddy simulations of bubbly flows and breaking waves with smoothed particle hydrodynamics

For turbulent bubbly flows, multi-phase simulations resolving both the liquid and bubbles are prohibitively expensive in the context of different natural phenomena. One example is breaking waves, where bubbles strongly influence wave impact loads, acoustic emissions and atmospheric-ocean transfer, but detailed simulations in all but the simplest settings are infeasible. An alternative approach is to resolve only large scales, and model small-scale bubbles adopting sub-resolution closures. Here, we introduce a large eddy simulation smoothed particle hydrodynamics (SPH) scheme for simulations of bubbly flows. The continuous liquid phase is resolved with a semi-implicit isothermally compressible SPH framework. This is coupled with a discrete Lagrangian bubble model. Bubbles and liquid interact via exchanges of volume and momentum, through turbulent closures, bubble breakup and entrainment, and free-surface interaction models. By representing bubbles as individual particles, they can be tracked over their lifetimes, allowing closure models for sub-resolution fluctuations, bubble deformation, breakup and free-surface interaction in integral form, accounting for the finite time scales over which these events occur. We investigate two flows: bubble plumes and breaking waves, and find close quantitative agreement with published experimental and numerical data. In particular, for plunging breaking waves, our framework accurately predicts the Hinze scale, bubble size distribution, and growth rate of the entrained bubble population. This is the first coupling of an SPH framework with a discrete bubble model, with potential for cost-effective simulations of wave–structure interactions and more accurate predictions of wave impact loads.

A physics-driven Σ-Y atomization model for heavy-duty engine simulations

The atomization of a liquid jet is a multi-scale and multi-physics problem of interest for many engineering applications. Particularly, it drives the fuel-oxidizer mixing and dictates the efficiency of combustion engines. High-fidelity multi-phase simulations remain challenging due to the excessive computational cost required to capture all the atomization scales. Thus, atomization models are necessary to represent sub-grid liquid structures. In this work, a modified Σ-Y model in the context of Eulerian-Lagrangian Spray Atomization (ELSA) is used to transport the surface area density of the spray. The model's predictive performance is assessed under various operating conditions relevant to heavy-duty engines using the Engine Combustion Network (ECN) Spray C and Spray D research-grade injectors. The classic droplet collision formulation of the Σ-Y model alone does not replicate the response of the measured spray surface area to changes in injector, ambient pressure, and injection pressure, requiring individual tuning of the model's parameters. Instead, a transition between dense and dilute spray breakup mechanisms is proposed in terms of the average droplet spacing. The collision breakup mechanism represents the dilute spray, whereas the droplet size in the dense spray is driven by a competition between the integral scale of turbulence and the balance between the turbulent kinetic energy and the surface energy of the droplets. Such an approach minimizes the requirements for model tuning. Moreover, the role of the constants of a compressible standard k-ε RANS model is assessed in the injector's internal flow and external spray simulation framework, and an updated set is proposed. The results are validated against x-ray radiography and Ultra-Small Angle X-ray Scattering (USAXS) data and highlight the predictive capabilities of the proposed physics-driven Σ-Y model, which is compatible with engine simulation turnaround times.

Novel classification of multistage flash desalination via finite and infinite flashing: Investigating thermofluid dynamics under varying inlet flow rates employing validated multiphase CFD simulations

This research presents a comprehensive investigation into the flashing process within the evaporation zone of a multistage flashing (MSF) desalination chamber. It introduces a novel classification of the flashing process as ideal, finite, and infinite, aiming to advance the understanding of this critical phenomenon. A validated volume-of-fluid (VOF) multiphase computational model is employed to accurately predict the shape of the free surface and elucidate the complex phase change phenomena occurring within the MSF chambers. By systematically varying the inlet brine velocities and rigorously analysing the thermofluid behaviour in the flashing chamber under both finite and infinite flashing conditions, this study provides a comparative analysis of design factors, including flashing rate and maximum bubble nucleation. Additionally, non-equilibrium losses and flashing efficiency are examined as pivotal metrics for evaluating the flashing process. The findings reveal distinct behaviours of the evaporation zone for finite and infinite flashing processes. Intriguingly, alterations in the flow rate lead to simultaneous enhancements and detriments in thermal efficiency due to the intricate interplay of turbulence promotion, improved mixing, and reduced residence time. Furthermore, the study highlights the significant impact of the inlet flow rate on phase change size, flashing rate, and bubble nucleation frequency within the bubble formation region. This investigation emphasizes the critical importance of comprehending the flashing phenomena and its consequential effect on the thermal efficiency of MSF systems. Leveraging advanced computational models, this study provides a solid foundation for identifying innovative methodologies to optimize the flashing process and enhance the overall performance of MSF systems. The ground-breaking insights presented in this research contribute significantly to the scientific understanding of the field and pave the way for future advancements in MSF desalination technology.

An engineering model for the pyrolysis of materials

Accurately representing the time dependent heat release rate of fuels is critical to performance-based design in fire safety applications. Existing simplified models either use average pyrolysis rates at different heat fluxes or do not account for the change in burning behavior at higher heat transfer rates. This paper presents the theoretical basis of a scaling-based pyrolysis model, S-Pyro. The model is based on the concept of maintaining the shape of a reference heat release rate per unit area curve but scaling the magnitude and time based on a dynamic thermal exposure. The model has been implemented in the computational fluid dynamics software Fire Dynamics Simulator (FDS). The model is validated with solid-phase only and multi-phase simulations of cone calorimeter experiments. The solid-phase simulations evaluated the capability of the model to predict the heat release rate per unit area of 149 materials tested at heat fluxes other than the reference flux. Multi-phase simulations of bench-scale fire experiments with a single material, Canada Pine and Spruce plywood, were used to evaluate the performance of the pyrolysis model in FDS. The model uncertainty was lower for high heat release rate materials, with the model uncertainty approaching the experimental uncertainty at higher burning rates.